Vol. 4 No. 2 (2024): African Journal of Artificial Intelligence and Sustainable Development
Articles

The Impact of AI-Driven Energy Efficiency Solutions on Sustainable U.S. Manufacturing

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  • Dr. Emma Clarke
Dr. Emma Clarke
Lead AI Scientist, DeepMind, London, UK

Published 09-09-2024

Keywords

  • Energy Efficiency,
  • Manufacturing
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

[1]
Dr. Emma Clarke, “The Impact of AI-Driven Energy Efficiency Solutions on Sustainable U.S. Manufacturing”, African J. of Artificial Int. and Sust. Dev., vol. 4, no. 2, pp. 209–231, Sep. 2024, Accessed: Dec. 22, 2024. [Online]. Available: https://africansciencegroup.com/index.php/AJAISD/article/view/161

Abstract

In this study, we provide a comprehensive analysis of the effect of AI-driven energy efficiency solutions on the promotion of sustainable manufacturing, focusing on the U.S. economy. Our approach combines economic growth and pollution impact, allowing us to shed light on the role of AI applications. The associated rebound effect is also considered. The analyses show that AI-informed plant-level energy savings result in lower energy costs for firms. Lower costs combined with higher demand leads to increased output. The basic and more realistic models analyze the three parallel factors: increased output, the substitution effect whereby lower fuel prices increase fuel use (negative), and the energy savings effect which brings only a partial reversal.

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References

  1. Sengottaiyan, Krishnamoorthy, and Manojdeep Singh Jasrotia. "Relocation of Manufacturing Lines-A Structured Approach for Success." International Journal of Science and Research (IJSR) 13.6 (2024): 1176-1181.
  2. Gayam, Swaroop Reddy. "Artificial Intelligence for Natural Language Processing: Techniques for Sentiment Analysis, Language Translation, and Conversational Agents." Journal of Artificial Intelligence Research and Applications 1.1 (2021): 175-216.
  3. Nimmagadda, Venkata Siva Prakash. "Artificial Intelligence for Compliance and Regulatory Reporting in Banking: Advanced Techniques, Models, and Real-World Applications." Journal of Bioinformatics and Artificial Intelligence 1.1 (2021): 151-189.
  4. Putha, Sudharshan. "AI-Driven Natural Language Processing for Voice-Activated Vehicle Control and Infotainment Systems." Journal of Artificial Intelligence Research and Applications 2.1 (2022): 255-295.
  5. Sahu, Mohit Kumar. "Machine Learning Algorithms for Personalized Financial Services and Customer Engagement: Techniques, Models, and Real-World Case Studies." Distributed Learning and Broad Applications in Scientific Research 6 (2020): 272-313.
  6. Kasaraneni, Bhavani Prasad. "Advanced Machine Learning Models for Risk-Based Pricing in Health Insurance: Techniques and Applications." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 170-207.
  7. Kondapaka, Krishna Kanth. "Advanced Artificial Intelligence Models for Predictive Analytics in Insurance: Techniques, Applications, and Real-World Case Studies." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 244-290.
  8. Kasaraneni, Ramana Kumar. "AI-Enhanced Pharmacoeconomics: Evaluating Cost-Effectiveness and Budget Impact of New Pharmaceuticals." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 291-327.
  9. Pattyam, Sandeep Pushyamitra. "AI-Driven Data Science for Environmental Monitoring: Techniques for Data Collection, Analysis, and Predictive Modeling." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 132-169.
  10. Kuna, Siva Sarana. "Reinforcement Learning for Optimizing Insurance Portfolio Management." African Journal of Artificial Intelligence and Sustainable Development 2.2 (2022): 289-334.
  11. Gayam, Swaroop Reddy, Ramswaroop Reddy Yellu, and Praveen Thuniki. "Artificial Intelligence for Real-Time Predictive Analytics: Advanced Algorithms and Applications in Dynamic Data Environments." Distributed Learning and Broad Applications in Scientific Research 7 (2021): 18-37.
  12. Nimmagadda, Venkata Siva Prakash. "Artificial Intelligence for Customer Behavior Analysis in Insurance: Advanced Models, Techniques, and Real-World Applications." Journal of AI in Healthcare and Medicine 2.1 (2022): 227-263.
  13. Putha, Sudharshan. "AI-Driven Personalization in E-Commerce: Enhancing Customer Experience and Sales through Advanced Data Analytics." Journal of Bioinformatics and Artificial Intelligence 1.1 (2021): 225-271.
  14. Sahu, Mohit Kumar. "Machine Learning for Personalized Insurance Products: Advanced Techniques, Models, and Real-World Applications." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 60-99.
  15. Kasaraneni, Bhavani Prasad. "AI-Driven Approaches for Fraud Prevention in Health Insurance: Techniques, Models, and Case Studies." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 136-180.
  16. Kondapaka, Krishna Kanth. "Advanced Artificial Intelligence Techniques for Demand Forecasting in Retail Supply Chains: Models, Applications, and Real-World Case Studies." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 180-218.
  17. Kasaraneni, Ramana Kumar. "AI-Enhanced Portfolio Optimization: Balancing Risk and Return with Machine Learning Models." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 219-265.
  18. Pattyam, Sandeep Pushyamitra. "AI-Driven Financial Market Analysis: Advanced Techniques for Stock Price Prediction, Risk Management, and Automated Trading." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 100-135.
  19. Kuna, Siva Sarana. "The Impact of AI on Actuarial Science in the Insurance Industry." Journal of Artificial Intelligence Research and Applications 2.2 (2022): 451-493.
  20. Nimmagadda, Venkata Siva Prakash. "Artificial Intelligence for Dynamic Pricing in Insurance: Advanced Techniques, Models, and Real-World Application." Hong Kong Journal of AI and Medicine 4.1 (2024): 258-297.
  21. Selvaraj, Akila, Praveen Sivathapandi, and Rajalakshmi Soundarapandiyan. "Blockchain-Based Cybersecurity Solutions for Automotive Industry: Protecting Over-the-Air (OTA) Software Updates in Autonomous and Connected Vehicles." Cybersecurity and Network Defense Research 3.2 (2023): 86-134.
  22. Paul, Debasish, Gunaseelan Namperumal, and Akila Selvaraj. "Cloud-Native AI/ML Pipelines: Best Practices for Continuous Integration, Deployment, and Monitoring in Enterprise Applications." Journal of Artificial Intelligence Research 2.1 (2022): 176-231.
  23. Namperumal, Gunaseelan, Sharmila Ramasundaram Sudharsanam, and Rajalakshmi Soundarapandiyan. "Data-Driven Workforce Management in Cloud HCM Solutions: Utilizing Big Data and Analytics for Strategic Human Resources Planning." Australian Journal of Machine Learning Research & Applications 2.2 (2022): 549-591.
  24. Soundarapandiyan, Rajalakshmi, Yeswanth Surampudi, and Akila Selvaraj. "Intrusion Detection Systems for Automotive Networks: Implementing AI-Powered Solutions to Enhance Cybersecurity in In-Vehicle Communication Protocols." Cybersecurity and Network Defense Research 3.2 (2023): 41-86.
  25. Sudharsanam, Sharmila Ramasundaram, Praveen Sivathapandi, and Yeswanth Surampudi. "Cloud-Based Telematics and Real-Time Data Integration for Fleet Management: A Comprehensive Analysis of IoT-Driven Predictive Analytics Models." Journal of Artificial Intelligence Research and Applications 3.1 (2023): 622-657.
  26. Prabu Ravichandran. “Implements and Integrates Data-Centric Applications Based on Big Data Analysis Service on Big Data Platforms”. International Journal on Recent and Innovation Trends in Computing and Communication, vol. 12, no. 2, Sept. 2024, pp. 848-55

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